We provide a full range of services required to design, develop, and implement AI solutions for new or existing products and business processes. Our approach focuses on transforming business operations through end-to-end custom AI-driven solutions that optimize workflows and operational efficiency. 

AI Solutions Development Services  includes:

• AI Implementation Consulting
• AI governance and control
• Full cycle development of AI enabled solutions 
• Deployment and operation of agentic AI systems
• AI models development (LLMs, Computer Vision, ML), data pipelines, MLOps setup 
• Continuous ModelOps and optimization
• Cost, quality, and performance monitoring

At SOFYCOD we are providing service for formation and management of AI engineering teams tailored to long term goals of our customers. This is not simple outstaffing this is formation of autonomous engineering team capable conduct delivery without any micro  management from customer’s side. Such teams this is real engineering extension of customer’s engineering team. 

When we are forming and managing dedicated AI engineering team we conduct following steps:

• Precise selection, interviews and testing of candidates with deep evaluation of their technical knowledge and personal qualities  
• Constant control of engineering processes, code quality standards, and delivery governance
• Ensuring that engineers uses Cursor, Copilot, Builder.io, v0 by Vercel, Amazon Q Developer and other AI based tools for increasing speed and quality of delivery
• Full leadership: planning, execution, reporting, and risk control
• Creating environment for constant professional growth, long-term expertise growth inside the team and knowledge transfer

We assess your business challenge, data readiness, and technical landscape to define the right AI strategy, roadmap, and implementation approach — including PoCs, tooling, and integration planning. AI readiness assessment (business, data, systems, resources):

• Discovery stage. Business Case definition, project vision, budget 
• AI readiness assessment: data, processes, IT infrastructure
• Use-cases, priorities, KPIs, Feasibility, forecasting ROI and economic impact for business
• Roadmap for 6–12 months, budgets, resources, infrastructure
• Architecture, UI design, software requirements, design of AI core, data sets, AI models selection 
• PoC for selected top use cases, AI implementation
• Delivery of an implementation plan with prioritized use cases and proven technology choices to fast-track your AI Journey

Average duration of this process is 4–6 Weeks as described in our AI-Driven Development Framework